readme
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.env.example
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.env.example
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POSTGRES_HOST=192.168.0.200
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POSTGRES_PORT=5432
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POSTGRES_DB=fbla
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POSTGRES_USER=postgres
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POSTGRES_PASSWORD=postgrespw
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JWT_SECRET=CHANGE_ME
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BASE_URL=https://fbla26.marinodev.com
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EMAIL_HOST=marinodev.com
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EMAIL_PORT=465
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EMAIL_USER=westuffind@marinodev.com
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EMAIL_PASS=CHANGE_ME
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FBLA26_PORT=8000
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BODY_SIZE_LIMIT=10MB
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LLAMA_PORT=8001
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LLAMA_HOST=192.168.0.200
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LLAMA_MODEL=Qwen3VL-2B-Instruct-Q4_K_M.gguf
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LLAMA_MMPROJ=mmproj-Qwen3VL-2B-Instruct-Q8_0.gguf
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README.md
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README.md
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# sv
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# CareerConnect - FBLA 2025
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Everything you need to build a Svelte project, powered by [`sv`](https://github.com/sveltejs/cli).
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## Overview
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## Creating a project
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This is a lost and found application built using [SvelteKit](https://kit.svelte.dev/) for the 2026 FBLA Website Coding &
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Development event. It allows users to browse items, post found items, and manage them. The
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application is designed for fast performance and a seamless user experience.
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If you're seeing this, you've probably already done this step. Congrats!
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## Features
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- User authentication (login/signup/logout)
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- Email-only token-based methods for non-admins
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- Browse/search items
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- Post found items
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- Inquire about items
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- Claim items
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- Email notifications
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- Themes
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## Installation
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To set up the project locally, follow these steps:
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### Prerequisites
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- [Node.js](https://nodejs.org/) (LTS recommended)
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- [npm](https://www.npmjs.com/) or [pnpm](https://pnpm.io/)
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### Clone the repository
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```sh
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# create a new project in the current directory
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npx sv create
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# create a new project in my-app
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npx sv create my-app
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git clone https://git.marinodev.com/MarinoDev/FBLA25
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cd FBLA25
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```
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## Developing
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Create a `.env` file in the root directory and configure environment variables. `.env.example` is provided as a
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template.
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Download a LLaMA compatible LLM (and mmproj) to `llm-models`. I
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recommend [Qwen3-VL-2B-Instruct](https://huggingface.co/Qwen/Qwen3-VL-2B-Instruct-GGUF).
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Once you've created a project and installed dependencies with `npm install` (or `pnpm install` or `yarn`), start a development server:
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### Docker
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A `Dockerfile` and `docker-compose.yml` file are provided for running the application in a Docker container.
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### Manual
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Using Docker is strongly recommended, as it bundles the database and the AI.
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#### Install dependencies
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```sh
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npm install
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```
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#### Start the development server
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```sh
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npm run dev
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# or start the server and open the app in a new browser tab
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npm run dev -- --open
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```
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## Building
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Go to `http://localhost:5173/` (or the port shown in the terminal).
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To create a production version of your app:
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## Deployment
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To deploy the application, build it using:
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```sh
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npm run build
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node build
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```
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You can preview the production build with `npm run preview`.
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## Resources Used
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### Technologies
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- [SvelteKit](https://kit.svelte.dev/)
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- [Tailwind CSS](https://tailwindcss.com/)
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- [Shadcn (Svelte version)](https://www.shadcn-svelte.com)
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### Libraries
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- [dotenv](https://www.npmjs.com/package/dotenv)
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- [bcrypt](https://www.npmjs.com/package/bcrypt)
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- [desm](https://www.npmjs.com/package/desm)
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- [nodemailer](https://www.npmjs.com/package/nodemailer)
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- [jsonwebtoken](https://www.npmjs.com/package/jsonwebtoken)
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- [postgres.js](https://www.npmjs.com/package/postgres)
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- [lucide](https://www.npmjs.com/package/@lucide/svelte)
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- [sharp](https://www.npmjs.com/package/sharp)
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- [valibot](https://www.npmjs.com/package/valibot)
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> To deploy your app, you may need to install an [adapter](https://svelte.dev/docs/kit/adapters) for your target environment.
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@ -34,9 +34,9 @@ services:
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- ./llm-models:/models:ro
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command:
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- -m
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- /models/Qwen3VL-2B-Instruct-Q4_K_M.gguf
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- /models/${LLAMA_MODEL}
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- --mmproj
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- /models/mmproj-Qwen3VL-2B-Instruct-Q8_0.gguf
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- /models/${LLAMA_MMPROJ}
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- --host
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- 0.0.0.0
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- --port
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